The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Quick and timely identification of endpoint network issues is critical for wireless network administrators to meet service level agreement requirements. However, existing computer-implemented diagnostic tools are limited in the types of data available and the format that the data is presented in. For example, some device management tools only display a client device's current state, with limited to no historical data. To access the historical data, network administrators often need to use a separate set of tools featuring data logs to properly identify the source of connectivity issues. Thus, a burden is placed on network administrators to access numerous diagnostic tools in a piecemeal fashion to properly monitoring the network. The complexity and inconvenience of using numerous fragmented tools to identify and correct network issues wastes both time and resources.
Furthermore, rich integrated historical views have not been present in traditional Graphical User Interfaces (GUIs) due to the limited storage capabilities of wireless controllers. Existing diagnostics usually are done using limited GUI or command line utility tools that lack a fully integrated, rich visualization. For example, some tools merely present a data log table that network administrates are forced to manually sort through to identify root causes of network connectivity problems. Manual sorting of data across multiple tools is inefficient and often ineffective for correctly and timely identifying network issues.